OpenTSDB is an open-source, distributed time series database designed to monitor large clusters of commodity machines at an unprecedented level of granularity. OpenTSDB enables operations teams to keep track in real-time of all the metrics exposed by operating systems, applications and network equipment, and makes the data easily accessible.
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The art of dealing with real-time data is not new. In fact, much of the world's economy is propped up my making decisions on data sub milliseconds. The technology is there, we have the power. We'll take a whirlwind tour of the open-source Esper system and understand how to integrate it into your stack to enable rapid decision making on real-time data from anywhere in your architecture.
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This talk introduces an open-source SQL-based system for continuous or ad-hoc analysis of streaming data built on top of Flume-based data collection for Hadoop.
Attendees will understand how to use a new tool to extend their Hadoop data collection pipeline with real-time streaming analytics.
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In this talk, we will introduce a simple formula for all Big Data applications: Big Data = Fast Data + Deep Data. Through a use-case format, we will discuss the specialized requirements for real-time (“fast”) and analytic (“deep”) data management.
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We'll present the architecture and implementation of a Node.js/DTrace-based distributed platform for analyzing the performance of cloud applications in real-time. We'll do a live demo on a real, internet-facing cloud and discuss some of the interesting performance pathologies we've found and explained using this tool.
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